A recommendation engine for cafés

The aim of the project is to develop a recommendation system for customers in a cafe with mobile devices. QR code activates the menu and meanwhile the recommendation algorithm executes. The menu comes with recommendation labels. The customer orders from the menu and rate the items ordered while leaving. Collaborative filtering is popular among recommendation systems. However, it has some problems like dependency on human ratings, sparsity and cold start problem. In this project, we designed hybrid recommender system by combining user-based & memory-based collaborative filtering and some other techniques. As a result, we overcame the drawbacks of the collaborative filtering.